The Fed's Bank Stress Test Is Wrong

Summary

• I believe that the Fed is well-intentioned and is unwilling to see a repeat of the Great Recession, but its Bank Stress Test is wrong.
• Why did Quantitative Easing and Geithner’s “Wall of Money” work?
• I explain in very simple and clear terms how an investor should interpret loss analytics, and what type of questions to ask of the CRO.
• Can the banks hold up if we are heading into arecession?

Some Basics in Loss Analytics

Based on over a decade of my work in Commercial Mortgage Backed Securities (CMBS) and some Residential (RMBS) loss modeling, the generic loss profile is depicted in Fig. 1. Yes, I figured out how to calculate Black Swans. I have named Fig. 1, the Risk Centerfold as it depicts all useful measures of risk in relation to each other based on my first-hand experience working these metrics. Loss risk is the probability distribution of losses in dollars, given a specific reference condition, that a default has occurred and must not include $0 losses.

As Fig. 1 shows, most losses are centered around the mode or peak of the distribution. The average or mean μ loss is always to the right of this mode as depicted by 1x. Occasionally, the losses are so large (Var, CVaR & Black Swans) they can be many times greater than the mean as this distribution is skewed to the right; i.e. the right tail is very long.

VaR or Value at Risk as a Measure of Extreme Loss (MEL – my term to facilitate clarity and bury all the complexities in loss analytics) is more frequently used in trading and rarely in securitization. VaR is usually set at the 98^th percentile. The mortgage securitization industry (i.e. bonds) uses a MEL of 3x. In very simple terms this MEL value is used to determine the risk capital, a financial institution needs to have available to it in the eventuality of an adverse economic environment.

This loss distribution will shift to the right in adverse times and economies. Banks and companies do fold in good times, too, you know. If this shift to the right is significant, MELs can evolve into Black Swans. The problem with Black Swans is that they are summative and tend to domino. For the economy to be resilient to crashes, we need in place anti-domino mechanisms. Right now, my guess is as good as yours as to what those mechanisms would be. Halting an exchange is not it. Nor is more legislation. What is required is something that is market-driven.

How did the 3x MEL come about? As far as I could figure out, it has its origins in the Normal distribution. Early in the industry, losses were considered Normally distributed, and thus had symmetrical tails. It so happened that the standard deviations σ of these loss distributions were approximately equal to their means μ. Thus 1x, 2x and 3x were equivalent to number of standard deviations away from the mean μ and 3x would be approximately 3σ or 98%. The world has moved on, but the mortgage securitization industry still holds on to its old ways.

Fig. 1: The Risk Centerfold (Source: Ben Solomon 2017)

As one can see, the MEL of 3x falls far short of the MEL of VaR which is around 5x to 7x, and therefore underestimates the “real” MEL. I have termed this the Blindsided Methodology Risk, the risk we don’t measure because our statistic is short-sighted. Personally, I prefer CVaR, Conditional Value at Risk, because it is much more stable than VaR; however, it is 10x computationally more intensive than VaR.

Assuming that risk capital is set aside to cushion unexpected losses, how does this MEL cushion work? Very simply and elegantly, risk capital shifts the loss distribution to the left. That is why, Timothy Geithner, the Secretary of the Treasury during the Great Recession, used a “Wall of Money” to substantially reduce the risk to the economy. See Stress Test. Yes, Quantitative Easing was the right thing to do at that time. It was a very innovative and powerful mechanism to transfer cash to the banks and shift the banks’ loss risk distributions to the left.

Note, however, risk capital only converts “unabsorbable” losses to absorbable losses and does not change the risk profile of the bank. Risk capital is a balance sheet play, while the risk profile (shape of the loss distribution) is an income play. Therefore, to infer a bank’s risk profile I would suggest using Income Before Fees per unit of Assets (IBFA).

What About the Fed’s Bank Stress Test?

The point of any stress test is to ensure that the company undergoing the test survives a severely adverse environment. Therefore, MEL cannot be some average “bad” number but should be the worst possible outcome, say 98% of the time. The June 21, 2018, Stress Test shows that bank capital would fall 4.4% from 12.9% to 7.9%. What 4.4%? Wait a minute, that was a result I was getting when I was new to CMBS VaR & CVaR loss analytics in 2003. Another bank (I’m not allowed to reveal their name) I knew, with a young risk team had 3% - they had not taken into account the long tail. I had to check.

Using the latest Fed’s Bank Stress Test results (their model is very thorough but don’t mistake thoroughness for correctness) I compiled what the Feds used for their Severely Adverse case versus worst scenarios in recent history. I ignored the really big test of 1929 as the Fed had ignored that, too. I didn’t bother with their Adverse case. Just using the statistics I’m familiar with, the tables below show what actually happened in recent history versus what the Fed used.

Table 1: GDP Growth – is grossly underestimated
Actual				Stress GDP
From	1Q78	16.40%		From	3Q17	3%
To	1Q80	-8%		To	2Q18	-9%
	Change	-24.40%			Change	-12%
Table 2: S&P/Case-Shiller U.S. National Home Price Index (data limited) – probably underestimated as California had much higher loss rates of -40.9% between 3Q 2006 and 2Q 2012.
Actual				Stress Test
From	Jul-01	184.6		From	4Q2017
To	Feb-12	134.0		To	3Q2019
	Change	-27.41%			Change	-30%
Table 3: Unemployment – may be OK
Actual				Stress Test
From	May-79	5%		From	4Q2017	4%
To	Apr-83	11%		To	3Q2019	10%
	Change	-6%			Change	-6%

Click to enlarge

The Fed’s Bank Stress Test does underestimate worst-case outcomes. Here is why:

1. Primary Flaw: Statistical models tend to revert to the mean, i.e. these provide averages not outliers as is required of long tails.
2. Not Handling Catastrophes: Catastrophes occur when a few unrelated events come together. (Look up Malcolm Gladwell’s Outliers). Therefore, using statistical input models to determine related inputs severely reduces the possibility of worst-case events coming together.
3. What Risk Methodology?: It is not clear what risk methodology the Fed is using. Though not documented, my initial inference was that the Fed may have used a 1x, 2x, 3x approach, but I could not even find that. I infer that the Bank Stress Test originated in 2009, in the rush to calm the public, just after the Wall Street Crash of 2008, and during the Great Recession. The Fed cobbled together some econometric models and showed an output that said everything was okay. That cobble is now the standard.
4. Missing Distribution: There are no Monte Carlo outputs, and the Fed report does not discuss what percentile the 4.4% belongs to. Imagine you have $13.1 trillion in assets and you don’t even discuss what percentile 4.4% belongs to?

The Correct Approach to Stress Testing

The correct approach to conducting a stress test is to frame the problem in terms of when the bank will default and then work backwards to determine what it takes to keep the bank solvent. The Feds avoid both these questions.

The next step is to identify the range of input values for each input variable. Determine their probability distributions or at least state your distribution assumptions. Determine possible correlations between inputs but be careful how this is factored in.

Recall that the loss distribution is based on a specific reference condition, the default, and that loss must be greater than $0. Similarly, in bank stress test, the reference condition is, bank default is eminent when bank capital declines below some specific value; say 5%, and when the economy is good. The lower this number, the safer the bank! Why do I say, “when the economy is good”? Because stress testing is about whether the bank (or for that matter any organization) will hold up, going from a great economy to an adverse one.

Also note that capital structure is primarily about the bank’s cost of maintaining that capital. The free market does not care what you paid for that structure, just that you pay.

Feed these input data into a bank Monte Carlo model. Plot the distribution of the statistic of interest –bank capital and only when that capital is below that reference value. Determine the additional capital, below this reference condition, required to cover the 98^th percentile worst case.

Therefore, the Fed’s Bank Stress Test should report three parameters,

1. CapSolv: Minimum capital required to keep a bank solvent in good times. CapSolv is the reference default condition for bank stress testing. It shows how well a bank’s leverage is structured, after all they are borrowing from the public.
2. CapAbv: Capital required above/greater than CapSolv, required to cushion losses in good times, as banks do fold in good times, too. Reported at the 98^th percentile. CapAbv shows how well they can weather a rash of bad events (e.g. major borrower like Enron, WorldCom, GM . . . going bust, etc.) in good times. CapAbv should be similar across banks as it is very much an indicator of factors in the external economy. I won’t be surprised if there are regional or state variations in this statistic.
3. CapRisk: Risk capital required to cushion losses in adverse times, reported at the 98^th percentile. CapRisk shows how risky the bank’s policies are. Given that CapSolv < CapAbv < CapRisk, a bank’s capital structure must be at least that of CapRisk.

Very good banks have very low CapSolv, and the smaller the difference between CapRisk and CapAbv for a given CapSolv, the better the bank’s risk profile.

I believe that the Fed is well-intentioned and unwilling to see a repeat of the Great Recession, but from a risk perspective, I have no idea what the Feds are reporting with the Bank Stress Test. It is irrelevant as it is wrong.

What Should Investors Ask at Investor Meetings?

You don’t attend an investors’ meeting and ask the Chief Risk Officer if his trucks are reliably maintained to deliver goods? Or if his warehouse can securely hold the commodities, he is long on? Do you? No kidding, I actually heard that on a conference call. Those are questions for the COO.

The following are sample risk-focused questions to ask.

1. How did you arrive at your MEL figures?
2. How stable are your MEL figures?
3. How have you physically implemented your MEL cushion?
4. By how much would these MEL estimates increase if the economy deteriorated?
5. Could these losses evolve into Black Swans?
6. What cash flow management (not cash flow reporting or forecasting) do you have in place and how frequently does your management team review this? (A US Bank study found that 83% of corporate failures show up as cash flow problems i.e. cash flow is on the frontline of detecting problems.)
7. How does adding the new product alter your MEL and what precautions have you taken to mitigate possible losses?
8. What is the lowest capital the bank or financial services company can operate with, without defaulting on its obligations?
9. What is your Net Income Before Fees per dollar of Assets? And how does it compare with other banks in your peer group?

What Should Investors Do?

Go back to the basics. Look at the banks’ Net Interest Margin (NIM) and Income Before Fees per Assets (IBFA), after all that is the primary purpose of banks. They are the intermediaries of funds, borrow from one group and lend to another. Note getting to IBFA is not easy as it requires a lot of digging. Compare with their peers. If it is higher than its peers, find out why. The answer maybe that they have riskier assets and borrowers are likely to readjust, i.e. it is not sustainable. If lower, again find out why. Are they growing by discounting?

Obviously by now, you know that I am an independent thinker and neither a conformist nor a contrarian. With that in mind here is a proposal on how to analyze bank stocks, without the benefit of knowing their fee income.

Bear in mind this is a quick and dirty analysis only. Using Friday’s (12/28/2018) closing prices, I put together a quick analysis of the 7 biggest US banks. See Table 4.

For banks, gross profit which is interest income is essentially revenue. Thus, revenue per dollar of asset is a measure of the riskiness of the bank assets assuming risk-reward is linear.

Table 4: Bank Data	Chase	BofA	Wells Fargo	Citigroup	Goldman Sachs	Morgan Stanley	US Bancorp
Revenue ($B)	93.689	83.956	85.989	64.277	32.073	37.945	20.038
Gross Profit ($B)	93.689	83.956	85.989	64.277	28.636	34.061	20.038
Share price ($)	96.83	24.39	45.78	51.83	163.03	39.37	45.21
Market Cap ($B)	321.954	239.368	215.497	126.576	60.642	67.722	73.063
MktCap($B)/Asset($B)	0.1271	0.1049	0.1104	0.0687	0.0661	0.0795	0.1581
Assets($B)	2,534	2,281	1,952	1,842	917	852	462
Gross Profit / Assets	3.70%	3.68%	4.41%	3.49%	3.12%	4.00%	4.34%

Click to enlarge

Source: Yahoo Finance 2018, bank data based on latest annual filings.

Okay, this is difficult to make sense of, right? Draw graphs, then the picture becomes clearer.

Fig. 2: Revenue versus Assets (Source: Ben Solomon 2018)

Fig. 2 depicts revenue produced by bank assets. It is clear that all banks behave similarly. For every dollar of assets, they generate $0.0376 of revenue. Therefore, revenue growth is achieved by asset growth, not by product innovation. That is, there are no scale efficiencies to be gained at this end of the banking segment.

Fig. 3: Revenue per Asset versus Total Assets (Source: Ben Solomon 2018)

From Fig. 3 Wells Fargo (WFC), US Bancorp (USB) and Morgan Stanley (MS) were generating more revenue per asset than their peers, which means their assets were riskier than the baseline risk banks of Goldman Sachs (GS), Citigroup (C), BofA (BAC) and Chase (JPM).

Fig. 4: Market Cap per Asset versus Revenue per Asset (Source: Ben Solomon 2018)

However, Fig. 4 shows that as of Friday close, the market was rewarding BofA, Chase and US Bancorp a share price premium over the other 4 banks (Goldman Sachs, Citigroup, Morgan Stanley and Wells Fargo). As such these 4 banks - Goldman Sachs, Citigroup, Morgan Stanley and Wells Fargo - are likely to move in tandem. US Bancorp is an island on its own, high risk and high rewards. With Morgan Stanley the market has factored in its risk, and it performs like the others.

This is about BofA versus Chase. Both share prices should lower, otherwise risk arbitrage is present. It is more likely that Chase's share price will decline to be equivalent to BoFA’s and match the risk profiles of the other banks and not BofA's share price increasing to match the equivalent of Chase.

Analyst’s Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Comments

[User 7557291]

Increased bank regulation the past 10 years has allowed tremendous growth in the "shadow banking" system, non-bank lenders, private credit hedge funds, etc. They aren't subject to that (or as much) regulation. The risks of collapse there may not be as systemic of a risk, due to being spread across a lot of little firms with high net worth investors who can ostensibly absorb the losses. But my concern with over regulating the TBTF banks without also taking action to curtail excesses in other forms of lending, would be that we allow the shadow banking world to get too big-- the outsized risks still being taken, just under a different umbrella.

[Benjamin Solomon]

@Protovision

I think the shadow banking is a good thing, since, as you said, it spreads the risk at the same time limiting this risk to a wealthier population who can absorb the losses.

Its not about how much or how little regulation we have. Our regulations need to be market savvy which they are not. Having said that I believe all financial services companies, whether shadow or not should be governed by two primary sets of regulations:

1. All financial services companies, are required to have MEL cushions, figure out their loss characteristics and publish these results, even if they are privately held as we need the visibility to prevent the domino of black swans. That is the primary regulation we need.

2. I addressed this in an earlier comment, that when a financial services company fails, if it is necessary as in the case of banks, its capital is wiped out and a new set of shareholders take over, with the stipulation that no bank can be a substantial shareholder of the new company.

[Benjamin Solomon]

@liquorisquicker

First, I don't buy that legislation can prevent a massive meltdown like 2008.

It hasn't happened as you have shown. It just keeps politician satisfied that they have "done something" to "fix" the problem. And the record stands - the laws have failed to prevent crashes. That is like King Canute (www.medievalists.net/...) commanding the waves to go back.

The MEL cushion or bailout is a stop-gap measure. It makes unabsorbable losses absorbable but it does not change the banks risk profile, which is the shape of the loss distribution.

Breaking up the banks reduces the size of the Black Swan at each bank and gives the Fed/Govt. time to rectify bit by bit in small pieces.

The US economy is not a homogeneous structure. I found this out some years ago and the numbers I quote are from memory. The leading edge of a recession is driven by the big states, California, New York, Florida and Texas(?). Colorado lags by about 6 to 9 months. Rhode Island by about 18 to 24(?) months. All states are in between these time lags.

That gives the Fed/Govt time to resolve solvency issues small doses at a time, state by state, on a first-come-first-serve basis. Fed/Govt. takes over, and stabilizes it balance sheet. The shareholders of the insolvent bank lose everything.

The Fed/Govt. hands it off to a private investor’s group to turn the bank around. They sell the new turned-around bank to the highest bidder. The subsequent sale is a very important requirement. With the sale the Fed gets paid back its stabilizing funds with interest.

The public can see that the Fed/Govt. is handling the issues and gearing for the next bank failure. This will give the public confidence.

Bottom line we need a market mechanism that "mops up" (for the want of a better term) bank failure, without creating massive banks. As the data in my article suggests, there are no benefits to the economy to have massive banks, at worst these have massive Black Swans.

[SayItWithLyrics]

@Benjamin Solomon

You seem to be agreeing with me, but doing everything possible to convince yourself you aren't.

-- We agree that the Federal Govt is the ultimate backstop for the big banks
-- We agree that backward looking regulation has done nothing to prevent the "next crash"
-- We agree that if TBTF banks are the cause of economic black swans, then the govt should be breaking them up now instead of waiting for the next black swan

So what is it that we don't agree on?

The implication of the govt being the ultimate backstop is that they have to define what level of tail risk they can absorb, and then all your risk charts work back from there.

If you accept the implied premise of the last point, which is that many smaller banks are less vulnerable to simultaneous tail risk than a few large ones, than that change would also fundamentally change your graph of risk profile.

[Benjamin Solomon]

@liquorisquicker

Yes, we agree don't we.

Yes, the risks will change, the tails get shorter.

[Benjamin Solomon]

liquorisquicker, very simply put, when a loan defaults, the bank forecloses and sells the property. If the amount owing is less than the selling price, there is no loss and the difference should be returned to the owner. If the amount owing is more, then if the loan is non-recourse, then bank absorbs the losses. That loss will always be much smaller than the original loan amount. Unless it was a predatory lending loan.

Yes, the Fed & Govt are the "lender of last recourse", but the US economy is a free market economy, there is no law that says the Fed or the Govt. should bail out the banks.

I believe that if we have another banking failure like what happened during the Great Recession, the Govt should say, enough is enough, and break up the banks. Unless the Govt. itself, push come to shove, does not believe in the free market.

[SayItWithLyrics]

@Benjamin Solomon

What we saw in 2008 is exactly the kind of cascading risk that defines black swan events. Euphoria quickly became panic, and the value of the underlying assets (houses) collapsed so what seemed like safe mortgages because disasters. It was no different that what happened in the Panic of 1893 and subsequent economic depression, except the one in the 1890s was cause by the collapse in the value of railroads. Because there was no govt (or Fed) backstop in the 1890s, unemployment got to 15-20%, there were riots in the cities, and farmers were wiped out. People starved to death. And if you had asked the bankers in 1892, I'm sure they all would have told you their loans were adequately collateralized.

So whether there are laws or not about bailing out banks, there is little choice but to in 2019 and beyond as the risk of doing nothing is worse than the cost of a bailout (politically and economically). So the govt (and Fed) are the bank backstop, like it or not. And with each event, they add news regulations / laws to try to avoid the next one.

The problem is that they keep closing the barn door behind the last horse that bolted instead of looking forward to what is likely to be the next one. I guess that is the definition of politics. If the result of the next financial black swan is to break up the big banks (I'm not sure I agree with that premise, but let's use it as an example), why aren't we breaking them up now to avoid it?

[SayItWithLyrics]

I like the thought process, but I'm struggling with the notion that Stress Tests should be aimed at the worst possible case. That would mean a capital ratio of 1:1 -- cash to cover all loans going bad. It is like telling borrowers they have to have the full value of the loan they are taking in a bank account in order to be able to borrow.

I think the statistics have to work the other way. Ultimately the Fed and the Federal Govt are the backstop for the ultimate Black Swan. What is the risk they are willing to take on, and how does that translate into the risk that the banks must take on?

[Knowledge helps !]

It started as a very interesting article, but ended with some wrong interpretations of the graphs... US Bancorp is not high risk, high return...its payment business is high revenues/ assets.....

[Benjamin Solomon]

Knowledge helps !, I'm glad you have a different opinion, as a healthy functioning market requires heterogeneous investor expectations. My findings, in 1995, across 10 maybe 15 (forget exact number) stock markets around the world showed that markets crash when investor expectations homogenize. Fear is the universal homogenizer of investor expectations.

I did say that this section was a quick and dirty approach and that one has to take out the fee income. This section was written to illustrate how to infer the riskiness of a bank's assets in the absence of a working Bank Stress Test model.

Re US bank, yes, and high returns implies high risk, except in this case competitors have not figured out, just yet, how to break down the barriers that maintain these high returns for US Bank. Watch out for the new entrants.

At the end of the day you have to break out the various banking components and see what is what, and make your own decisions that match your risk profile.

[dynx]

Those are the worst “best fit” lines in a scatter graph I’ve ever seen.
Anybody can draw a random line anywhere and claim that point A should be below it. I’d like to see the math that created the lines. No math? No point.

[dynx]

To go further you could say based on the progression of graphs that MS and WF are undervalued based on a best fit rather than a baseline. Why is the baseline the baseline for value? Why isn’t revenue growth included as a forward looking indicator? So much missing.

[Benjamin Solomon]

I'm glad you disagree.

I did say that this section was a quick and dirty approach and that one has to take out the fee income. This section was written to illustrate how to infer the riskiness of a bank's assets in the absence of a working Bank Stress Test model.

There rest is your homework.